The present invention relates to a method for characterizing patterns.
The manual characterization of samples by people is a time-consuming and expensive process. In order to speed up this process, methods are used which generate a characterization proposal. The processing employee must either accept the proposal or modify it if the proposal is not correct. Characterization methods are used in particular in classification methods in which a set of parameters for identifying objects is determined using training examples. The training data record must representatively cover all the peripheral conditions of the identification task here. In order to identify street scenes, samples of several thousand to tens of thousands of manually processed images containing all the potentially occurring classes of objects, for example passenger cars, trucks, two-wheeled vehicles, pedestrians, weather conditions etc., are required.
From the processing of colored video images, a method is known in which an object, for example a tree, is characterized manually in the first image in an image sequence (J. R. Ohm, P. Ma: “Feature-Based Cluster Segmentation of Image Sequences”, Int. Conf. on Image Processing, Vol. III, 1997, pages 178-181). With this predefined information an attempt is made to identify again the same object in the next image of the image sequence. In this context, the color information of the object is preferably used to distinguish the object from the rest of the image. This method is not suitable for gray value images. The manual processing of the object is very time-consuming during the characterization process.
A method is known (A. K. Jain, Yu Zhong, S. Lakshamanan, “Object matching using deformable templates”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 18, No. 3, March 1996, p. 267-278) in which a database of automatically generated contour patterns is used to characterize objects (patterns) in image data. The contour patterns are automatically adapted to the objects and superimposed on them. The image data together with the contour patterns superimposed on them are then presented to a viewer on a screen.